Axial Bearing Capacity Of Piles Research Articles

The decrease of the bearing capacity of single pile foundation during earthquake on liquefiable soil (Study Case: Birobuli Area, South Palu)

Birobuli is located South Palu, Indonesia. In Indonesia, earthquakes are frequent events. Consequently, it is crucial to consider the safety of building structures against earthquakes when calculating the factor of safety of the building. It is important to not only analyse the impact of earthquakes on the superstructure but also take into account their effect on the substructure. One potential substructure failure caused by earthquakes is soil liquefaction, which refers to a decrease in soil bearing capacity resulting from seismic activity. To assess this phenomenon, a quantitative approach was employed in this study, involving soil investigations and sampling from the field. The findings from the soil investigation were used to calculate the susceptibility of soil liquefaction in different soil layers and the axial bearing capacity of single pile foundations both before and during earthquake and liquefaction. The study site predominantly consisted of silty sand with ground water table (GWT) level at -4m with low CPT value, making it susceptible to liquefaction from depths ranging between -4 meters and -12 meters. Two single pile models were simulated in the study, with respective reductions in their axial pile bearing capacity of 71,6% and 38,9%

ИССЛЕДОВАНИЕ НЕСУЩЕЙ СПОСОБНОСТИ СВАЙ НА ОСНОВЕ ЭМПИРИЧЕСКИХ ДАННЫХ, ДИНАМИЧЕСКИХ ИСПЫТАНИЙ И ЧИСЛЕННОГО МОДЕЛИРОВАНИЯ

Axial bearing capacity is an important factor in designing of foundation. It must be able to carry the load of upper structure without any significant deformation due to important role in pile design. A part from empirical and numerical methods, axial pile bearing capacity can be predicted by pile driving analyzer test that use wave equation analysis during the test. Prediction of the axial bearing capacity and its distribution can be achieved by combining wave equation analysis with dynamic pile monitoring. This paper compares the axial capacity of pile obtained from PDA records with predicted axial capacities obtained using empirical, numerical, and interpretation of static load test method. The empirical method used NSPT data from bore testing that conduct in site, finite element method that uses in this study is Plaxis 8.6. Both of them was compared with PDA test result of axial bearing capacity. There is a difference value of the calculation results of axial pile bearing capacity and foundation settlement. Comparing with PDA, from empirical method has smallest deviation for axial bearing capacity which equal to -268.45 kN with percentage -6.05%, smallest settlement equal to 0,0044 m. Plaxis result shows that distinction between Qult result equal to -11.00 kN with percentage -0.24% and settlement of foundation equal to 0,005 m. From interpretation of static loading test method smallest deviation for Qult which equal to -40,00 kN, with percentage -0,90%, and smallest settlement equal to 0,0055 m. So, from all method the smallest deviation for Qult and PDA result is used finite element method. This is due to many data parameters has been inputted and analyzed in the Plaxis program, so the results of calculation analysis are more detailed and closer to the situation in the research site. Differences in axial bearing capacity can be caused by the test was carried out which depends on the accuracy of operator and parameters that used in the calculations.

Analisis Penurunan Daya Dukung Tiang Tunggal pada Tanah yang Berpotensi Mengalami Likuifaksi di Kota Denpasar, Bali

In Indonesia, earthquakes occur very frequently. As a result of the earthquake, the safety of building structures against earthquakes really needs to be taken into account in the analysis of calculating the factor of safety. Apart from the effect of the earthquake on the superstructure, the effect of the earthquake on the substructure must also be considered. One of the substructure failures that can occur in the substructure due to an earthquake is a soil liquefaction where the soil experiences a loss/decrease in the bearing capacity of the soil as a result of the earthquake. This study used a quantitative method by conducting soil investigations and taking soil samples from the field. The results of the soil investigation will be used in calculating the potential for liquefaction of the soil layers and the axial bearing capacity of single pile foundations before and during liquefaction. At the study site, the dominant soil is loose sand with a high ground water table. The soil has the potential to experience liquefaction from a depth of 1.5 m to 13 m. This study modeled 2 pile models where both of them experienced a decrease in the axial pile bearing capacity respectively: 93% and 79%.

Reliability analysis of pile foundations: peculiarities of consideration of uncertainties and partial factors

Pile foundations are used to transmit construction loads deep into the ground, thus ensuring the stability of the structure. In this context, there is no question that the calculation of pile bearing capacity is important in the design of economical and safe geotechnical structures. Typically, the axial bearing capacity of piles can be determined using five approaches. At the same time, under real conditions, the effectiveness of these approaches is limited, firstly, by the restrictions inherent in their computational apparatus and, secondly, by the action of a variety of uncertain and random factors. Meanwhile, in geotechnics the uncertainties are largely unknown or very difficult to measure. In view of the above, the aim of the article is to develop a methodology for analyzing the reliability of a pile foundation taking into account uncertainties and partial factors. The methodological basis of the research is a comprehensive approach, which includes the analysis and synthesis of literary data on the topic of work, analytical and experimental research. In the process of research an algorithm based on the Monte-Carlo method and the evolutionary neural network, which allows in the process of calculating the reliability of piles to take into account such uncertainties as: physical, statistical and modeling uncertainties. The conducted tests showed that the model has a high prediction accuracy. The theoretical value of the obtained results consists in the development of the pile foundation reliability evaluation apparatus due to the use of neural network modeling. In practice, the recommendations formulated in the article can be used as a basis for conducting experiments with pile foundations in various soil sciences conditions.

Uncertainty Analysis of Axial Pile Capacity in Layered Soils by the Piezocone Penetration Test

This study presented a framework for uncertainty analysis of the ultimate axial bearing capacity of piles evaluated by the UniCone method in layered soils. The UniCone method by Eslami and Fellenius (1997) is a direct piezocone penetration test (CPTU) method for evaluating the ultimate axial capacity of piles in the reliability design. The spatial variability of CPTU data is modeled as a random field for each soil unit in the soil strata. The empirical correlation coefficients of the UniCone method are assumed to follow lognormal distributions. On the basis of uncertainties of CPTU data and empirical correlation coefficients, the first-order reliability method (FORM) is then applied to the reliability analysis of ultimate axial bearing capacity of piles. The effects of spatial variability of CPTU data and variations of empirical correlation coefficients on the ultimate axial bearing capacity of piles are evaluated by an Excel spreadsheet-based framework. Seven case studies show that the proper identification of different soil units from soil profiles is crucial for estimating the failure probability of pile capacity in the reliability analysis. Uncertainties of CPTU data and empirical correlation coefficients would be over-estimated unless different soil units in soil profiles are identified properly from each other. The over-estimated geotechnical parameters contribute to a higher failure probability of pile capacity. The proposed framework can evaluate the uncertainty of the ultimate axial bearing capacity of pile foundations more rationally.

Optimized selection of axial pile bearing capacity predictive methods based on multi-criteria decision-making (MCDM) models and database approach

Optimized selection of axial pile bearing capacity predictive methods based on multi-criteria decision-making (MCDM) models and database approach

Relevant data-based approach upon reliable safety factor for pile axial capacity

Pile foundations are one of the significant marine substructure systems for a variety of offshore and onshore facilities. Thus, optimum and reliable design during their lifetime and under inherent uncertainties is noteworthy. Among various methods for predicting axial pile bearing capacity, cone penetration test (CPT)-based methods enhance geotechnical design to a more satisfying level due to continuous and reliable CPT records and their suitable performance in offshore environments. This article aims to reveal the importance of CPT and pile databases, especially in deltaic deposits. A new relevant CPT and pile data-based approach is introduced by assessing a few elaborated works on typical CPT and pile case studies. The proposed procedure assists in comparing the characteristics and conditions of a given pile with similar database cases through screening and, consequently, deciding on the design methods' priority. It is depicted that superior methods result in a more reliable design and higher resistance factors and efficiency ratios in load and resistance factor design (LRFD). Accordingly, it is engaged with lowered safety factors in the allowable stress design (ASD) approach. Eventually, upon various assessment criteria, the optimum site-specific methods are proposed leading to a performance-based design that can be realized in geotechnical practice.

Statistical Evaluation of CPT and CPTu Based Methods for Prediction of Axial Bearing Capacity of Piles

Piles are structural members made of steel, concrete, or wood installed into the ground to transfer superstructure loads to the soil. Nowadays, many structures are built on poor lands, and therefore piles have crucial roles in such structures. Performing in-situ tests such as cone penetration (CPT) and piezocone penetration tests (CPTu) have always been of great importance in designing piles. These tests have a brilliant consistency with reality, and as a result, the outcome data can be used in order to achieve reliable pile designing models and reduce uncertainty in this regard. In this paper, the capability of various CPT and CPTu based methods developed from 1961 to 2016 has been investigated using four statistical methods. Such CPT and CPTu based methods are adopted for direct prediction of axial bearing capacity of piles using CPT and CPTu field data. For this purpose, 61 sets of field data prepared from CPT and CPTu have been collected. The data sets were utilized in order to calculate the axial bearing capacity of piles (QE) through 25 different methods. In addition, the measured axial pile capacities (QM) have been collected, recorded and prepared from field static load tests, respectively. Then, four different statistical approaches have been applied to assess the accuracy of these methods. Finally, the most reliable and accurate methods are presented.

Probabilistic Assessment of Model Uncertainty for Prediction of Pile Foundation Bearing Capacity; Static Analysis, SPT and CPT-Based Methods

Geotechnical designs, like other engineering disciplines, are always accompanied by uncertainties. Supplying continuous and reliable records and reducing the uncertainty associated with measurement errors, the cone penetration test (CPT) enhances the geotechnical designs to a more decent level. Deep foundation design, as an essential challenge of foundation engineering, is also involved with different sources of uncertainty. Moreover, the presence of various design methods, relying on different assumptions and requirements, introduces further complications to the selection of an appropriate method, which leads to the broad spectrum of the predictions. Hence, a database, including 60 driven pile load test results and CPT records in the vicinity of them, was compiled to investigate the model uncertainties embedded in various predictive approaches. Investigated approaches include two static analyses, five SPT, and five CPT-based methods, and were implemented to predict axial pile bearing capacity. The model parameters for these methods are investigated through seven statistical, probabilistic, and reliability-based criteria. Performance of the methods under these criteria is assessed by the use of radar charts. Moreover, the resistance factor, adopted in this study to estimate the efficiency ratio and actual factor of safety, is calibrated by four different prevailing methods. Eventually, among conventional available predictive methods, CPT-based methods perform better than others and result in cost-effective and optimized trends.

Prediction of Pile Axial Bearing Capacity Using Artificial Neural Network and Random Forest

Axial bearing capacity of piles is the most important parameter in pile foundation design. In this paper, artificial neural network (ANN) and random forest (RF) algorithms were utilized to predict the ultimate axial bearing capacity of driven piles. An unprecedented database containing 2314 driven pile static load test reports were gathered, including the pile diameter, length of pile segments, natural ground elevation, pile top elevation, guide pile segment stop driving elevation, pile tip elevation, average standard penetration test (SPT) value along the embedded length of pile, and average SPT blow counts at the tip of pile as input variables, whereas the ultimate load on pile top was considered as output variable. The dataset was divided into the training (70%) and testing (30%) parts for the construction and validation phases, respectively. Various error criteria, namely mean absolute error (MAE), root mean squared error (RMSE), and the coefficient of determination (R2) were used to evaluate the performance of RF and ANN algorithms. In addition, the predicted results of pile load tests were compared with five empirical equations derived from the literature and with classical multi-variable regression. The results showed that RF outperformed ANN and other methods. Sensitivity analysis was conducted to reveal that the average SPT value and pile tip elevation were the most important factors in predicting the axial bearing capacity of piles.

Physical Modelling of Axial Compressive Bearing Capacity of Instrumented Piles in Oil-Contaminated Sandy Soil

Oil and its derivatives such as gasoline, gasoil and ‎kerosene are the main sources of energy in the transport and industry sectors, and also the most common ‎soil contaminants. Oil contamination of the soils as a serious geoenvironmental problem not only affects soil quality ‎but also changes its geotechnical properties. Any changes in the geotechnical properties of the soils affect the axial bearing capacity of pile. The main objective of the current study is to determine the effects of various concentrations of different oil ‎products, as well as different soil relative densities, and thickness of the contaminated sand layer on the load–displacement (axial compressive) behaviour of two ‎instrumented, close-ended steel pipe piles with different diameters and slenderness ratios implemented in an oil-contaminated sandy soil through physical modelling. Tests results were compared with the CFEM ‎analytical method of calculating pile axial bearing capacities. Results showed that increasing the percentage of the oil in the soil reduces the values of net total, toe and shaft bearing ‎capacity of the pile. The type of the oil had a remarkable effect on the bearing capacities of the pile. The higher the kinematic ‎viscosity, the lower the amount of bearing capacities. ‎Comparing the measured and predicted values of bearing capacity based on modified CFEM ‎method concluded that, although a good agreement can be seen between the results of shaft capacity, the ‎CFEM method with modified bearing capacity factors could not predict the effects of oil contamination ‎on the toe bearing capacities of piles precisely.

Reliability based assessment of axial pile bearing capacity: static analysis, SPT and CPT-based methods

ABSTRACT Since piles are one of the major geotechnical foundation systems, estimation of their axial bearing capacity is of great importance. Employing different design methods, resulting in a wide range of bearing capacity estimations, complicates the selection of an appropriate design scheme and confirms the existence of model error along with the inherent soil variability in bearing capacity prediction. This paper tends to evaluate different predictive methods in Reliability-Based Design (RBD) framework. In this regard, different static analyses, SPT and CPT-based methods are considered to evaluate which approaches collectively and which method individually, have more reliable predictions for compiled data bank. In order to assess reliability indices and resistance factors, two approaches have been considered, i.e. First Order Second Moment method (FOSM) and First Order Reliability Method (FORM). To investigate the reliability indices for different methods in both RBD approaches, various safety factors and loading ratios have been considered. Also, the Load and Resistance Factor Design (LRFD) resistance factors are calibrated for different target reliability indices and loading ratios. Results show that CPT-based methods are more reliable among other methods. Furthermore, the estimated efficiency ratio, i.e. the ratio of resistance factor to resistance bias factor, confirms this agreement.

FE-based identification of pile–soil interactions from dynamic load tests to predict the axial bearing capacity

The static axial pile bearing capacity depends mainly on the developed pile–soil interaction. Hence, to determine a realistic and reliable ultimate pile bearing capacity, the pile–soil interaction needs to be identified and described precisely. One relevant field for this application is dynamic load tests (DLTs). During a DLT, the pile bearing capacity is deduced from measurements at the pile head. Current procedures of deriving the bearing capacity of open-ended piles from these measurements are lagging behind regarding the description of the pile–soil interaction for open-ended piles and the influence of the pore fluid response. Hence, a new technique based on the finite element method is developed, which captures the key aspects for DLT results correctly and is capable of deriving the static pile bearing capacity. The method is validated against dynamic and static load test data obtained from centrifuge tests on large diameter monopiles. An application to field test data of tubular steel piles is shown. The developed approach seems suitable to assess the static pile bearing capacity based on DLT measurements.

A Method for Predicting Pile Capacity Using Cone Penetration Test Data

The massive construction in poor lands has encouraged engineers to use deep foundations in order to transfer superstructure loads to the subsoil. Since soil excavation, sampling, and laboratory testing as a part of site investigation are relatively difficult, in-situ tests such as cone penetration test (CPT) as a very informative test may be recommended. The CPT has been widely used in engineering as a part of site investigation, and its data has been used to determine the axial capacity of piles. In this paper, the prediction capability of three empirical widely famous old methods used to predict the axial pile capacity based on CPT data is evaluated by using field data obtained from direct field pile loading tests. In this evaluation, the direct pile load test results are used as measured data. Three popular famous statistical evaluation methods namely the best-fitted line, geometric mean, and geometric standard deviation have been used. The evaluation results indicate that generally although predicting methods based on CPT data have been widely used to determine the axial bearing capacity of piles, they need to be upgraded for the economic and relatively accurate design of piles. According to the statistical studies carried out in the current research, among three old empirical methods, although the Nottingham and Schmertmann Method (1975, 1978) (NSM) [7, 8] has the best agreement with test results, it is felt that the method needs to be upgraded. The modification of NSM has been done in the current paper using a comprehensive database.

Evaluation of axial pile bearing capacity based on pile driving analyzer (PDA) test using Neural Network

A few decades, many methods have been developed to predict and evaluate the bearing capacity of driven piles. The problem of the predicting and assessing the bearing capacity of the pile is very complicated and not yet established, different soil testing and evaluation produce a widely different solution. However, the most important thing is to determine methods used to predict and evaluate the bearing capacity of the pile to the required degree of accuracy and consistency value. Accurate prediction and evaluation of axial bearing capacity depend on some variables, such as the type of soil, diameter, and length of pile, etc. The aims of the study of Artificial Neural Networks (ANNs) are utilized to obtain more accurate and consistent axial bearing capacity of a driven pile. ANNs can be described as mapping an input to the target output data. The method using the ANN model developed to predict and evaluate the axial bearing capacity of the pile based on the pile driving analyzer (PDA) test data for more than 200 selected data. The results of the predictions obtained by the ANN model and the PDA test were then compared. This research as the neural network models give a right prediction and evaluation of the axial bearing capacity of piles using neural networks.

Application of an evolutionary-based approach in evaluating pile bearing capacity using CPT results

Predicting ultimate axial bearing capacity of pile foundations is an important and complicated problem in geotechnical engineering. Cone penetration test (CPT) is a reliable in situ test widely used in the analysis and design of pile foundations. In this study, new CPT-based axial pile bearing capacity models are presented for both cohesionless and cohesive soils using evolutionary polynomial regression (EPR), a branch of evolutionary approaches. A relatively comprehensive database is gathered and divided into training and testing sub-sets to avoid over-fitting. This database includes both coarse and fine grain soils, cone tip resistance and sleeve friction of CPTs, geometry and bearing capacity of piles. The presented models are compared to some previously published ones and their preferences are demonstrated statistically and probabilistically. Proper applicability of the models in predicting axial pile bearing capacity is then confirmed by field verification, compared to analytical and empirical models available in the literature.

Comparative Study on Prediction of Axial Bearing Capacity of Driven Piles in Granular Materials

Estimation of axial bearing capacity plays an essential role in pile design. A part from semi-empirical and numerical methods, axial bearing capacity of piles can be either predicted by means of a maintain load test or dynamic load test. The latter test is based on wave equation analysis and it is provided by Pile driving analyzer (PDA). Combination of wave equation analysis with dynamic monitoring of the pile can result in prediction of axial bearing capacity of the pile and its distribution. This paper compares the axial capacity of pile obtained from PDA records and maintain load test (static load test) with predicted axial capacities obtained using analytical, empirical and finite element analysis. From the results it is observed that axial bearing capacity derived from numerical modelling with the aid of the finite element code, Plaxis, is in a good agreement with estimated axial capacity through analytical-empirical methods, PDA, and maintain load test.

Prediction of the Axial Bearing Capacity of Piles by SPT-based and Numerical Design Methods

The prediction of the axial capacity of piles has been a challenge since the beginning of the geotechnical engineering profession. In recent years determining bearing capacity of piles from in-situ testing data as a complement of static and dynamic analysis has been used by geotechnical engineers. The Standard Penetration Test (SPT) is still the most commonly used in-situ test and pile capacity determination by SPT is one of the earliest applications of this test. On the other hand, the acceptance of numerical analyses in geotechnical problems is growing and finite element calculations are more and more used in the design of foundations. In this paper, different approaches for estimating the bearing capacity of piles from SPT data have been explained and compared with numerical method. Then, comparisons between numerical and empirical results are presented and discussed.

Numerical investigation of axial bearing capacity of piles embedded in sloping ground

In practice, piles may be constructed in sloping ground where the axial capacity of piles may be affected by the ground slope. This paper presents the effect of the ground slope geometry on the ultimate axial bearing capacity of vertical pile using numerical simulation based on Plaxis 3D Foundation software. The pile is assumed to consist of linear and elastic material. Various aspect ratios (L/D) for the pile have been considered. The soil behavior is modeled based on the Mohr Coulomb failure criterion. Loose and dense sand, and sandy clay have been used for numerical modeling. Interface elements have been applied to the pile-soil boundaries to accommodate the slip which may occur between these two materials. The simulation of the pile-soil system is first calibrated using available data from the field load tests on piles to ensure the validity of the constructed numerical modeling. Various shapes for the ground slope have been considered in analyses, including flat- sloping, uniformly sloping, all-around upward sloping, and all-around downward sloping ground. The results have shown that the pile axial capacity increases with increase in the value of the upward sloping. In contrast, the pile capacity decreases with increase in the downward sloping. From a provided data base, empirical expressions have been presented to take into account the slope shape effect on the pile capacity. It has been found that this empirical expression can be confidently used in practice to account for the ground sloping effect on the pile capacity. This expression may be used in conjunction with conventional methods based on the limit equilibrium approach. This is interesting since practicing engineers are well familiar with conventional methods calculating the pile axial capacity. Key words: Pile, ground slope, axial capacity, pile, Mohr Coulomb, numerical method, finite element, Mohr Coulomb failure criterion.

Bearing capacity of model piles driven into dense overconsolidated sands

Model piles were driven into dense siliceous sand samples and tested in a large calibration chamber. Axial tension and compression tests were performed on open-ended pipe piles. The objective of this research was to study the effect of overconsolidation on the bearing capacity of piles driven into dense sands representative of North Sea soil conditions. Emphasis was put on points of interest for the offshore petroleum industry in particular: dense to very dense normally consolidated (NC) and overconsolidated (OC) sands, unit end bearing and unit skin friction capacities, and comparison with tip resistances from cone penetration tests. Design parameters are proposed for computing the axial bearing capacity of piles driven into dense to very dense siliceous sands. They are compared with those given in the current American Petroleum Industry's Recommended Practice 2A document. A relationship between CPT cone resistance and ultimate unit end bearing and skin friction capacities of piles is also proposed.Key words: model test, dense sand, offshore pile driving, axial capacity, end bearing, skin friction, design parameters, cone penetrometer.